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Chinese Journal of Applied Ecology ›› 2016, Vol. 27 ›› Issue (10): 3273-3282.doi: 10.13287/j.1001-9332.201610.022

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Spatial differentiation and impact factors of Yutian Oasis’s soil surface salt based on GWR model

YUAN Yu-yun1, WAHAP Halik1,2*, GUAN Jing-yun1,3 , LU Long-hui1,3, ZHANG Qin-qin1,3   

  1. 1Ministry of Education Key Laboraotory for Oasis Ecosystem, Xinjing University, Urumqi 830046, China;
    2College of Resource and Environment Science, Xinjiang University, Urumqi 830046, China;
    3College of Tourism Management, Xingjiang University, Urumqi 830046, China;
  • Received:2016-03-14 Published:2016-10-18
  • Contact: * E-mail: wahap@xju.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Fundation of China (U1138303).

Abstract: In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.